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Since 1987 - Covering the Fastest Computers in the World and the People Who Run ThemFri, 09 Dec 2016 15:32:26 +0000en-UShourly1https://wordpress.org/?v=4.760365857Scaling the New Bar for Latency in Financial Networkshttps://www.hpcwire.com/2010/08/09/scaling_the_new_bar_for_latency_in_financial_networks/?utm_source=rss&utm_medium=rss&utm_campaign=scaling_the_new_bar_for_latency_in_financial_networks
https://www.hpcwire.com/2010/08/09/scaling_the_new_bar_for_latency_in_financial_networks/#respondMon, 09 Aug 2010 07:00:00 +0000http://www.hpcwire.com/?p=5163The bar for what qualifies as a fast connection or "low latency" networking has always been higher in finance than in other areas of corporate networking. It's never been quite this high, however.

]]>The bar for what qualifies as a fast connection or “low latency” networking has always been higher in finance than in other areas of corporate networking. It’s never been quite this high, however.

The increased use of innovative algorithmic-trading strategies has levied unprecedented pressure on financial firms to seek out and remove any possible delays that could threaten the successful execution of automated buy and sell orders. Significant time and resources are spent to achieve even modest, incremental improvements in latency at every point in the ecosystem of processes and systems that undergird algorithmic trading.

Managers of financial networks have found that the process of transporting data from one building to another is a common source of those delays. The fiber optic links between stock exchanges, alternative trading systems, colocation providers and information feeds all introduce additional latency into the system. Once, those amounts were deemed negligible — even in financial networking. Today, they are simply unacceptable.

Contemporary Trading’s Latency Intolerance

High-frequency trading (HFT) and other forms of algorithmic trading have emerged since the late 1990s. In all of them, a computer model has a predefined set of rules that automates the process of buying and selling. The computer receives various inputs from throughout the world (market data on price and volume, labor statistics, employment information, for example). The data is parsed and monitored in real time, and automated buy/sell decisions are executed according to how the model interprets the incoming intelligence.

Since the first trade to the market gets the best price, the delivery of a buy or sell order must be as fast as possible. Just a little more than a year ago, firms were concentrating on removing milliseconds from their network; today, a mere 250 nanoseconds make a difference.

The solution is not a matter of contacting the local phone company and deploying its most current high-bandwidth connection to the buildings that house an exchange. Even adopting the leading-edge, highest-speed model of router or multicore processor computer blades might not successfully address the financial world’s hypersensitivity to latency.

Traditionally, a firm has sought to improve its algorithimic trading processes by focusing first on the computer model itself. A lot of mathematicians have invested a lot of hours into tweaking the models that predict how the world is going to behave. Next, firms have sought to boost efficiency by optimizing the servers that process information against models, as well as the switches connecting those servers. More and more frequently, firms often locate or colocate clusters of computers in the financial exchanges themselves to root out proximity delays. Today, a firm’s various building-to-building transport connections are attracting attention from IT staffs.

It’s an entire ecosystem that must be optimized to wring as much latency as possible from algorithmic trading, and many financial firms now seek to take greater control over all of it.

From Buy to Build

Historically, when a financial firm required a connection between two buildings, it procured service from a phone company by ordering a circuit at a monthly fee, and the system would run through the phone company’s network, which typically would have some routing functionality for linking the two locations. Two key things have changed in the last few years.

One, algorithmic trading has crystallized scrutiny on the latency created every time traffic must pass through a router or take an indirect path to a central office. (It’s easy enough to quantify the sum of these delays; any member of the IT staff can look up the impact on the router.) Two, a combination of advances in optical technology that are specifically designed to eliminate latency, plus the lower costs and expanded availability of dark fiber, have enhanced a financial firm’s business case for building a dedicated infrastructure.

The performance gains are in the orders of magnitude — from 120 microseconds of latency for a carrier-provided service between buildings to 40 microseconds in a privately operated, optimized infrastructure. Service reliability can be enhanced with 24-by-7 monitoring predicated on the knowledge that 30 minutes of downtime to a financial firm can mean millions of dollars in lost revenue. The firm becomes more flexible to react and scale for new opportunities, as circuits can be turned up as needed. And it gains a path to continued innovation when partnering with vendors who understand the firm’s low-latency requirements and are under the gun to roll out enhancements to continually shave delays.

These developments have financial network managers asking, “Who can I partner with to sell me dark fiber, and what is the path that the fiber will take?” The ramifications of the answers are far-reaching. Financial firms must ensure that they are not sinking their money in a dark fiber route that snakes jaggedly under roads and up and down manholes, given the fact that eight inches of fiber can translate into a nanosecond of delay.

The next question is, “What is the latency of that path?” That answer demands an understanding of how optical transport works.

Getting into the Glass

There are four common optical networking functions where managers of financial networks often can realize game-changing efficiencies in latency budgets. When traffic beams across glass fiber, it encounters equipment that performs amplification, color conversion, dispersion compensation and regeneration. Each of these Wavelength Division Multiplexing (WDM) functions can be absolutely necessary to successfully carry out transport depending on the specific network environment, but each certainly also will inject some delay into the process. How much delay is something that financial managers must quantify and control if they are to squeeze every drop of latency from their end-to-end infrastructures.

Color conversion — In WDM optical networking, traffic is “transponded” — or, converted to a color of light — for delivery of a signal across a pair of glass fiber. Similarly, multiple colors of light are aggregated across a single fiber; multiple 10 Gbit/s services, for example, are “muxponded” into a single pair of fibers. Again, a financial network’s transponding and muxponding functions must be optimized for low-latency transport because conventional techniques such as Optical Channel Data Unit (ODU) encapsulation and thin film filters introduce too much delay.

Dispersion compensation — One of the ways that a traffic signal can degrade over the span of an optical link is “chromatic dispersion.” This is a phenomenon in which a signal effectively smears into a spectrum of hues, and it’s particularly common for data travelling at high speed. Installing kilometers of dispersion compensating fiber (DCF) has provided a remedy in some optical networks, but it’s not a wise approach in infrastructures supporting algorithmic trading. Latencies are too great. Optimized methods, like Fiber Bragg gratings, offer a low-latency alternative for counteracting chromatic dispersion.

Regeneration — Another method for preventing signal degradation over the course of a glass fiber connection is regeneration. Low-latency approaches to the function can help managers of financial networks claim significant efficiencies, because commonly deployed methods of regeneration produce considerable delay.

Conclusion

Contemporary finance is a race between markets. Firms are concerned with nanoseconds of latency in the processes and the systems that underlie algorithmic trading. Shaving eight inches of fiber equates to a one-nanosecond lead. Every element in a firm’s strategy is being evaluated for improvements, and optical fiber transport is targeted as a prime area for optimization.

]]>The Register’s Rik Myslewski reports that Intel’s silicon photonics group has demonstrated an optical interconnect that carries data at 50 gigabits per second (Gbps). The prototype consists of a transmitter chip containing four integrated lasers, an optical cable, and a receiver chip to demultiplex the data at the other end. According to Mario Paniccia at Intel, the key to the technology is have it all implemented in silicon, including the lasers themselves, which removes the expense and performance issues associated with discrete components. Today’s discrete optical devices, used in HPC and elsewhere, can transmit data at 40 to 100 Gbps, but cost hundreds of dollars. Myslewski writes:

When asked about today’s 40Gbps optical interconnects, Rattner laughed. “I didn’t look this morning to see what they’re selling for, but my guess is that they’re hundreds of dollar a port. Our goal is to get down to a dollar a port. That would be success for us.”

]]>https://www.hpcwire.com/2010/07/27/intel_demos_50_gbps_silicon_photonics_prototype/feed/05182Darkstrand Gives NLR the Businesshttps://www.hpcwire.com/2008/10/28/darkstrand_gives_nlr_the_business/?utm_source=rss&utm_medium=rss&utm_campaign=darkstrand_gives_nlr_the_business
https://www.hpcwire.com/2008/10/28/darkstrand_gives_nlr_the_business/#respondTue, 28 Oct 2008 07:00:00 +0000http://www.hpcwire.com/?p=6488Access to National LambdaRail's high-speed optical fiber network will soon be available for commercial businesses (and just in time for the biggest recession in decades).

]]>Access to National LambdaRail’s high-speed optical fiber network will soon be available for commercial businesses (and just in time for the biggest recession in decades). As I wrote in Tuesday’s feature story, half the capacity of the system has been set aside for commercial use and will start servicing those users early in 2009.

Darkstrand is the company that won the rights to broker the NLR capacity and is busily gathering customers. I spoke with Darkstrand CEO Michael Stein, who told me he is seeing a lot of early interest from some big-name firms in media, manufacturing, and financial services. While he couldn’t commit to any specific companies, he expects to roll out the first 3 or 4 customers in January.

The second part of the story is that Darkstrand will also manage technology transfers between the NLR-affiliated national labs/universities and businesses. As I mentioned in the article, this may seem like an odd combo, but taking advantage of high-speed networks often revolves around tools and workflows unfamiliar to businesses. And it certainly fits into the Council on Competitiveness’ notion of an “enabling function” that bridges industries with HPC technologies.

Whether Darkstrand is up to the task remains to be seen, but the ecosystem approach seems like a natural way to build synergies. (And with a super-hero name like Darkstrand, how could they fail?) A more skeptical view of this business model is elaborated by Stacey Higginbotham at the New York Times, who writes that network access and commercialization technologies are distinct products:

In theory, it’s neat. But Darkstrand doesn’t have an exclusive agreement to get technology out of national labs, and the idea of it as a pre-vetted commercialization partner doesn’t mean much when the actual commercialization gets under way. Many companies have existing development efforts at national labs, and there are many other venture capitalists and IP brokers who also offer similar services.

To be sure, HPC service brokers do exist, but most are part of the service structure of a particular OEM like HP or IBM. Bob Graybill’s new firm, Nimbus Services, which we highlighted in a recent article, is a company that provides a vendor-neutral approach and they’re definitely worth keeping an eye on. According Stein, Darkstrand’s offerings could dovetail nicely with Nimbus, which provides a business-to-business brokerage model for compute cycles, software and high-end expertise.

While the commercialization services side of the Darkstrand offering may be uncharted territory, leasing the multi-gigabit pipes seems like a more straightforward business. Here Stein’s strategy is to sign up some marquee customers in various verticals — media, financial services, manufacturing, and biotech. If those customers can exploit the advantages of NLR’s bandwidth, their competitors are sure to follow.

The best case scenario for Darkstrand is that NLR becomes the network platform of choice for commercial HPC and related businesses and as a result of the influx of revenue, its footprint becomes even larger and attracts even more customers. Since network consortium already has plans to jump to 40 Gbps pipes in 2009 and 100 Gbps a few years later, the bandwidth should remain in sync or slightly ahead of most commercial demand. With all the high-end infrastructure in place, NLR could became the foundation of a cloud computing platform for HPC.